class_docstr: Randomly drop some regions of feature maps.
  
   Please refer to the method proposed in `DropBlock
   <https://arxiv.org/abs/1810.12890>`_ for details.
  
  Args:
      drop_prob (float): The probability of dropping each block.
      block_size (int): The size of dropped blocks.
      warmup_iters (int): The drop probability will linearly increase
          from `0` to `drop_prob` during the first `warmup_iters` iterations.
          Default: 2000.
code: def extra_repr(self):
      return (
          f"drop_prob={self.drop_prob}, block_size={self.block_size}, "
          f"warmup_iters={self.warmup_iters}"
      )
  
file_path: mmdetection/mmdet/models/layers/dropblock.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from mmdet.registry import MODELS
label_desc: Use image node_id 4 for calling the DropBlock obj's underlying member method code with example usage: obj.extra_repr() and returns: str, self, str, self, str, self